from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 13.0 | 58.704322 |
| daal4py_KNeighborsClassifier | 0.0 | 5.0 | 35.517624 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 9.052083 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 48.677891 |
| KMeans | 0.0 | 11.0 | 30.953066 |
| daal4py_KMeans | 0.0 | 7.0 | 23.554425 |
| LogisticRegression | 0.0 | 1.0 | 9.642698 |
| daal4py_LogisticRegression | 0.0 | 1.0 | 2.843947 |
| Ridge | 0.0 | 0.0 | 1.101484 |
| daal4py_Ridge | 0.0 | 0.0 | 0.769390 |
| total | 0.0 | 48.0 | 40.890023 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.142 | 0.005 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.538 | 0.014 | 0.265 | 0.002 | See |
| 1 | KNeighborsClassifier | predict | 0.195 | 0.013 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 1.0 | 0.101 | 0.002 | 1.928 | 0.005 | See |
| 2 | KNeighborsClassifier | predict | 32.225 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 1.0 | 4.470 | 0.041 | 7.209 | 0.000 | See |
| 3 | KNeighborsClassifier | fit | 0.141 | 0.004 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.535 | 0.009 | 0.263 | 0.001 | See |
| 4 | KNeighborsClassifier | predict | 0.187 | 0.015 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 0.099 | 0.002 | 1.890 | 0.007 | See |
| 5 | KNeighborsClassifier | predict | 38.648 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 4.469 | 0.017 | 8.649 | 0.000 | See |
| 6 | KNeighborsClassifier | fit | 0.131 | 0.004 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.530 | 0.020 | 0.247 | 0.002 | See |
| 7 | KNeighborsClassifier | predict | 0.199 | 0.015 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 0.104 | 0.002 | 1.922 | 0.006 | See |
| 8 | KNeighborsClassifier | predict | 38.809 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 4.562 | 0.038 | 8.508 | 0.000 | See |
| 9 | KNeighborsClassifier | fit | 0.129 | 0.006 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.530 | 0.013 | 0.242 | 0.003 | See |
| 10 | KNeighborsClassifier | predict | 0.199 | 0.006 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 1.0 | 0.103 | 0.002 | 1.942 | 0.001 | See |
| 11 | KNeighborsClassifier | predict | 17.218 | 0.001 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 1.0 | 4.470 | 0.032 | 3.852 | 0.000 | See |
| 12 | KNeighborsClassifier | fit | 0.129 | 0.006 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.529 | 0.009 | 0.243 | 0.003 | See |
| 13 | KNeighborsClassifier | predict | 0.211 | 0.006 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 0.099 | 0.003 | 2.120 | 0.002 | See |
| 14 | KNeighborsClassifier | predict | 25.509 | 0.001 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 4.483 | 0.019 | 5.690 | 0.000 | See |
| 15 | KNeighborsClassifier | fit | 0.141 | 0.005 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.543 | 0.017 | 0.260 | 0.002 | See |
| 16 | KNeighborsClassifier | predict | 0.211 | 0.007 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 0.100 | 0.001 | 2.115 | 0.001 | See |
| 17 | KNeighborsClassifier | predict | 25.386 | 0.079 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 4.541 | 0.027 | 5.591 | 0.000 | See |
| 18 | KNeighborsClassifier | fit | 0.055 | 0.002 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.098 | 0.005 | 0.562 | 0.004 | See |
| 19 | KNeighborsClassifier | predict | 0.020 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.005 | 0.000 | 4.470 | 0.019 | See |
| 20 | KNeighborsClassifier | predict | 24.208 | 0.237 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.997 | 0.013 | 24.291 | 0.000 | See |
| 21 | KNeighborsClassifier | fit | 0.052 | 0.002 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.097 | 0.007 | 0.534 | 0.007 | See |
| 22 | KNeighborsClassifier | predict | 0.031 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.005 | 0.000 | 6.571 | 0.015 | See |
| 23 | KNeighborsClassifier | predict | 32.645 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 1.025 | 0.035 | 31.849 | 0.001 | See |
| 24 | KNeighborsClassifier | fit | 0.056 | 0.002 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.098 | 0.004 | 0.568 | 0.003 | See |
| 25 | KNeighborsClassifier | predict | 0.031 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.005 | 0.001 | 6.450 | 0.020 | See |
| 26 | KNeighborsClassifier | predict | 32.576 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 1.082 | 0.013 | 30.114 | 0.000 | See |
| 27 | KNeighborsClassifier | fit | 0.053 | 0.002 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.098 | 0.004 | 0.540 | 0.002 | See |
| 28 | KNeighborsClassifier | predict | 0.013 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.005 | 0.000 | 2.822 | 0.017 | See |
| 29 | KNeighborsClassifier | predict | 11.441 | 0.056 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 1.004 | 0.020 | 11.393 | 0.000 | See |
| 30 | KNeighborsClassifier | fit | 0.056 | 0.003 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.097 | 0.004 | 0.575 | 0.005 | See |
| 31 | KNeighborsClassifier | predict | 0.023 | 0.002 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.005 | 0.000 | 4.708 | 0.018 | See |
| 32 | KNeighborsClassifier | predict | 20.199 | 0.034 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.995 | 0.006 | 20.308 | 0.000 | See |
| 33 | KNeighborsClassifier | fit | 0.058 | 0.004 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.095 | 0.004 | 0.610 | 0.006 | See |
| 34 | KNeighborsClassifier | predict | 0.022 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.005 | 0.000 | 4.523 | 0.009 | See |
| 35 | KNeighborsClassifier | predict | 20.185 | 0.091 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 1.069 | 0.010 | 18.882 | 0.000 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 2.622 | 0.047 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.739 | 0.011 | 3.546 | 0.001 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 10.622 | 0.334 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.463 | 0.013 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.116 | 0.006 | 4.006 | 0.003 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 2.635 | 0.038 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.784 | 0.011 | 3.361 | 0.000 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 6.534 | 0.234 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.839 | 0.016 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.209 | 0.006 | 4.017 | 0.001 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 2.642 | 0.057 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.748 | 0.016 | 3.532 | 0.001 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.005 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 4.281 | 0.169 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 2.796 | 0.039 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.657 | 0.018 | 4.255 | 0.001 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 2.578 | 0.048 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.781 | 0.012 | 3.300 | 0.001 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 4.063 | 0.291 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.740 | 0.018 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.113 | 0.002 | 6.554 | 0.001 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 2.624 | 0.055 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.756 | 0.010 | 3.470 | 0.001 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 3.155 | 0.287 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.377 | 0.021 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.209 | 0.005 | 6.592 | 0.001 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 2.639 | 0.052 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.745 | 0.013 | 3.544 | 0.001 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 2.546 | 0.219 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 4.613 | 0.034 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.656 | 0.010 | 7.035 | 0.000 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.207 | 0.024 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.531 | 0.010 | 2.272 | 0.001 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 0.0 | 0.000 | 0.000 | 14.432 | 0.384 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.033 | 0.003 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 0.0 | 0.001 | 0.000 | 34.975 | 0.167 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.261 | 0.018 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.542 | 0.012 | 2.329 | 0.001 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 13.504 | 0.224 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.033 | 0.003 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 24.740 | 0.104 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.219 | 0.035 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.522 | 0.011 | 2.335 | 0.001 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 14.744 | 0.260 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.059 | 0.008 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.008 | 0.001 | 7.010 | 0.027 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.213 | 0.018 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.532 | 0.010 | 2.279 | 0.001 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 0.0 | 0.000 | 0.000 | 3.944 | 0.518 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.030 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 0.0 | 0.001 | 0.000 | 31.517 | 0.078 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.233 | 0.017 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.523 | 0.008 | 2.360 | 0.000 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 3.499 | 0.452 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.034 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 25.466 | 0.065 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.237 | 0.043 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.530 | 0.012 | 2.334 | 0.002 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 3.639 | 0.352 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.059 | 0.003 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.008 | 0.001 | 7.591 | 0.009 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans | fit | 0.023 | 0.019 | 10000 | 10000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.006 | 0.003 | 3.986 | 1.002 | See |
| 1 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.925 | 0.294 | See |
| 2 | KMeans | predict | 0.000 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.868 | 0.253 | See |
| 3 | KMeans | fit | 0.422 | 0.012 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 24.0 | NaN | 0.165 | 0.010 | 2.553 | 0.004 | See |
| 4 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.388 | 1.446 | See |
| 5 | KMeans | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.299 | 0.096 | See |
| 6 | KMeans | fit | 0.013 | 0.002 | 10000 | 10000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 16.0 | NaN | 30.0 | NaN | 0.004 | 0.001 | 3.123 | 0.074 | See |
| 7 | KMeans | predict | 0.001 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.680 | 1.069 | See |
| 8 | KMeans | predict | 0.000 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.840 | 0.320 | See |
| 9 | KMeans | fit | 0.156 | 0.006 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.081 | 0.003 | 1.936 | 0.003 | See |
| 10 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.701 | 0.336 | See |
| 11 | KMeans | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.271 | 0.056 | See |
| 12 | KMeans | fit | 0.150 | 0.005 | 10000 | 10000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.027 | 0.001 | 5.571 | 0.004 | See |
| 13 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.671 | 0.400 | See |
| 14 | KMeans | predict | 0.001 | 0.000 | 10000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.058 | 0.439 | See |
| 15 | KMeans | fit | 1.397 | 0.067 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 20.0 | NaN | 18.0 | NaN | 0.658 | 0.026 | 2.124 | 0.004 | See |
| 16 | KMeans | predict | 0.001 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.821 | 0.320 | See |
| 17 | KMeans | predict | 0.008 | 0.002 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.002 | 0.000 | 3.844 | 0.164 | See |
| 18 | KMeans | fit | 0.062 | 0.002 | 10000 | 10000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.026 | 0.001 | 2.388 | 0.003 | See |
| 19 | KMeans | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.924 | 0.415 | See |
| 20 | KMeans | predict | 0.001 | 0.000 | 10000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.416 | 0.247 | See |
| 21 | KMeans | fit | 0.401 | 0.030 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 27.0 | NaN | 22.0 | NaN | 0.338 | 0.044 | 1.187 | 0.023 | See |
| 22 | KMeans | predict | 0.001 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.734 | 0.337 | See |
| 23 | KMeans | predict | 0.005 | 0.003 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.002 | 0.000 | 2.592 | 0.351 | See |
| 24 | KMeans | fit | 0.668 | 0.013 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.359 | 0.011 | 1.863 | 0.001 | See |
| 25 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.137 | 0.345 | See |
| 26 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.689 | 0.369 | See |
| 27 | KMeans | fit | 35.895 | 0.000 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 16.064 | 0.041 | 2.234 | 0.000 | See |
| 28 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.623 | 0.218 | See |
| 29 | KMeans | predict | 0.001 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.198 | 0.077 | See |
| 30 | KMeans | fit | 0.563 | 0.008 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.313 | 0.006 | 1.801 | 0.001 | See |
| 31 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.919 | 0.512 | See |
| 32 | KMeans | predict | 0.001 | 0.001 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.465 | 0.935 | See |
| 33 | KMeans | fit | 14.711 | 0.007 | 1000000 | 1000000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 6.847 | 0.065 | 2.149 | 0.000 | See |
| 34 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.637 | 0.248 | See |
| 35 | KMeans | predict | 0.001 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.180 | 0.143 | See |
| 36 | KMeans | fit | 8.058 | 0.096 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 4.130 | 0.026 | 1.951 | 0.000 | See |
| 37 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.676 | 0.254 | See |
| 38 | KMeans | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.050 | 0.193 | See |
| 39 | KMeans | fit | 159.252 | 0.000 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 87.531 | 0.000 | 1.819 | 0.000 | See |
| 40 | KMeans | predict | 0.001 | 0.001 | 1000000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.843 | 1.008 | See |
| 41 | KMeans | predict | 0.004 | 0.003 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.002 | 0.000 | 2.584 | 0.384 | See |
| 42 | KMeans | fit | 7.222 | 0.059 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.935 | 0.022 | 1.836 | 0.000 | See |
| 43 | KMeans | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.754 | 0.828 | See |
| 44 | KMeans | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.631 | 0.249 | See |
| 45 | KMeans | fit | 50.579 | 0.000 | 1000000 | 1000000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 40.677 | 0.000 | 1.243 | 0.000 | See |
| 46 | KMeans | predict | 0.001 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.168 | 0.525 | See |
| 47 | KMeans | predict | 0.010 | 0.001 | 1000000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.002 | 0.000 | 5.673 | 0.032 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 15.528 | 0.065 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 15.674 | 0.089 | 0.991 | 0.000 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.365 | 0.631 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.837 | 0.317 | See |
| 3 | LogisticRegression | fit | 1.302 | 0.025 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 1.310 | 0.027 | 0.994 | 0.001 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.001 | 0.104 | 1.154 | See |
| 5 | LogisticRegression | predict | 0.003 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.004 | 0.001 | 0.621 | 0.062 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 0.051 | 0.002 | 1000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.034 | 0.002 | 1.501 | 0.007 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 1000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.613 | 0.693 | See |
| 2 | Ridge | predict | 0.000 | 0.000 | 1000 | 100 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.615 | 0.318 | See |
| 3 | Ridge | fit | 0.012 | 0.001 | 10000 | 10000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.008 | 0.004 | 1.587 | 0.234 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 10000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 1.246 | 0.899 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 10000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.758 | 0.459 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
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"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
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"dependencies_info": {
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